Landslide Monitoring and characterization

EO-based landslide monitoring applications analyze the temporal evolution of landslide-induced ground motions by exploiting ground motion information provided by InSAR and PSI techniques. These data can support the geological and kinematic interpretation of the slope instability affecting the observed areas, especially in built-up and densely urbanized slopes, where landslide indicators are difficult to recognize due to the presence of the urban fabric. Local-scale, long-term monitoring of displacements induced by specific slope movements, using EO satellite data integrated and compared with the available conventional ground-based instruments networks (e.g. topographic levelling, inclinometers, extensometers, GPS), allows the analysis of the temporal variability of landslide motions and kinematics. Besides the use of PSI technologies, conventional InSAR allows analysis not only of motion velocities exceeding the limitation of the PSI approaches (i.e. few tens of cm/yr), but also deformation trends significantly differing from the deformation model (e.g. linear) used during the multi-temporal PSI processing (e.g. non-linear and/or accelerated motion). A supplementary advantage of InSAR is the spatial coverage and the ability to detect the landslide limits with lower costs than with PSI. But InSAR analyses are very demanding and experience is needed to face 3D-problems, atmosphere deformations or phase unwrapping.

The availability of wide-bandwidth, high frequency, high resolution SAR data has resulted in better monitoring capabilities of space-borne remote sensing instruments. In particular, the COSMO-SkyMed and TerraSAR-X sensors in microwave X-band provide spatial resolutions one order of magnitude better than previously available satellite SAR sensors. This implies more information about ground surface displacements as well as improved landslide monitoring and slope instability investigation capabilities. Furthermore, the new ESA (European Space Agency) Copernicus mission Sentinel-1  have opened new possibilities for interferometric SAR applications thanks to systematic and regular SAR observations, an effective revisiting time of 6 days and regional-scale mapping capability (due to the TOPS acquisition mode).

Overall, this kind of monitoring and characterization activity can recognize precursors to landslide failures or identify variability of motion behaviour due to triggering factors such as prolonged or intense rainfalls, thus supporting the risk management process during both near-real and deferred time.